Search results for: dominant growth models

Authors: Pratiksha Dubey, Praveen Singh, Shantanu Sen Gupta, Anand K. Bachhawat

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5-oxoproline (pyroglutamic acid) is a cyclic lactam of glutamic acid. In the cell, it can be produced by several different pathways and is metabolized into glutamate with the help of the 5-oxoprolinase enzyme (OPLAH or OXP1). The inhibition of 5-oxoprolinase enzyme in mammals was found to result in heart failure and is thought to be a consequence of oxidative stress [1]. To analyze the consequences of 5-oxoproline accumulation more clearly, we are generating models for 5-oxoproline accumulation in yeast. The 5-oxoproline accumulation model in yeast is being developed by two different strategies. The first one is by overexpression of the mouse  -glutamylcyclotransferase enzyme. It degrades -glu-met dipeptide into 5-oxoproline and methionine taken by the cell from the medium. The second strategy is by providing high concentration of 5-oxoproline externally to the yeast cells. The intracellular 5-oxoproline levels in both models are being evaluated. In addition, the metabolic and cellular consequences are being investigated.

Keywords: 5-oxoproline, pyroglutamic acid, yeast, genetics

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Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Long Kim Vu, Ban Dang Nguyen

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In this paper, the finite element method (FEM) is utilized to simulate the comprehensive process including tightening, releasing and self-loosening of a bolt joint under transverse vibration. Following to the accurate geometry of helical threads, an absolutely hexahedral meshing is implemented. The accuracy of simulation process is verified and validated by comparison with the experimental results on clamping force-vibration relationship, which shows the sufficient correlation. Further analysis with different amplitude and frequency of transverse vibration is done to determine the dominant factor inducing the failure.

Keywords: bolt self-loosening, contact state, finite element method, FEM, helical thread modeling

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Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

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This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: Divya Palaniappan

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Early Childhood assessment tools must measure the quality and the appropriateness of a curriculum with respect to culture and age of the children. Preschool assessment tools lack psychometric properties and were developed to measure only few areas of development such as specific skills in music, art and adaptive behavior. Existing preschool assessment tools in India are predominantly informal and are fraught with judgmental bias of observers. The World of Discovery TM curriculum focuses on accelerating the physical, cognitive, language, social and emotional development of pre-schoolers in India through various activities. The curriculum caters to every child irrespective of their dominant intelligence as per Gardner’s Theory of Multiple Intelligence which concluded "even students as young as four years old present quite distinctive sets and configurations of intelligences". The curriculum introduces a new theme every week where, concepts are explained through various activities so that children with different dominant intelligences could understand it. For example: The ‘Insects’ theme is explained through rhymes, craft and counting corner, and hence children with one of these dominant intelligences: Musical, bodily-kinesthetic and logical-mathematical could grasp the concept. The child’s progress is evaluated using an assessment tool that measures a cluster of inter-dependent developmental areas: physical, cognitive, language, social and emotional development, which for the first time renders a multi-domain approach. The assessment tool is a 5-point rating scale that measures these Developmental aspects: Cognitive, Language, Physical, Social and Emotional. Each activity strengthens one or more of the developmental aspects. During cognitive corner, the child’s perceptual reasoning, pre-math abilities, hand-eye co-ordination and fine motor skills could be observed and evaluated. The tool differs from traditional assessment methodologies by providing a framework that allows teachers to assess a child’s continuous development with respect to specific activities in real time objectively. A pilot study of the tool was done with a sample data of 100 children in the age group 2.5 to 3.5 years. The data was collected over a period of 3 months across 10 centers in Chennai, India, scored by the class teacher once a week. The teachers were trained by psychologists on age-appropriate developmental milestones to minimize observer’s bias. The norms were calculated from the mean and standard deviation of the observed data. The results indicated high internal consistency among parameters and that cognitive development improved with physical development. A significant positive relationship between physical and cognitive development has been observed among children in a study conducted by Sibley and Etnier. In Children, the ‘Comprehension’ ability was found to be greater than ‘Reasoning’ and pre-math abilities as indicated by the preoperational stage of Piaget’s theory of cognitive development. The average scores of various parameters obtained through the tool corroborates the psychological theories on child development, offering strong face validity. The study provides a comprehensive mechanism to assess a child’s development and differentiate high performers from the rest. Based on the average scores, the difficulty level of activities could be increased or decreased to nurture the development of pre-schoolers and also appropriate teaching methodologies could be devised.

Keywords: child development, early childhood assessment, early childhood curriculum, quantitative assessment of preschool curriculum

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Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

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Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

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Authors: Luan Vardari, Dena Arapi Vardari

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The Balkan countries, known for their diverse landscapes and cultural heritage, face the dual challenge of promoting economic growth while addressing pressing environmental concerns. In recent years, the concept of green finance has emerged as a powerful tool to achieve sustainable development and mitigate the environmental impact of various sectors, including architecture. This extended abstract explores the untapped potential of green finance in architecture within the Balkan region and highlights its role in driving sustainable construction practices and fostering a greener future. The abstract begins by defining green finance and emphasizing its relevance in the context of the architectural sector in Balkan countries. It underlines the benefits of green finance, such as economic growth, environmental conservation, and social well-being. Integrating green finance into architectural projects is important as a means to achieve sustainable development goals while promoting financial viability. Also, delves into the current state of green building practices in the Balkan countries and identifies the need for financial support to further drive adoption. It explores the existing regulatory frameworks and policies that promote sustainable architecture and discusses how green finance can complement these initiatives. Unique challenges faced by Balkan countries are highlighted, along with the potential opportunities that green finance presents in overcoming these challenges. We highlight successful sustainable architectural projects in the region to showcase the practical application of green finance in the Balkans. These projects exemplify the effective utilization of green finance mechanisms, resulting in tangible economic and environmental impacts, including job creation, energy efficiency, and reduced carbon emissions. The abstract concludes by identifying replicable models and lessons learned from these projects that can serve as a blueprint for future sustainable architecture initiatives in the Balkans. The importance of collaboration and knowledge sharing among stakeholders is emphasized. Engaging architects, financial institutions, governments, and local communities is crucial to promoting green finance in architecture. The abstract suggests the establishment of knowledge exchange platforms and regional/international networks to foster collaboration and facilitate the sharing of expertise among Balkan countries.

Keywords: sustainable finance, renewable energy, Balkan region, investment opportunities, green infrastructure, ESG criteria, architecture

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Authors: Jaya Shrivastava

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The particle aspect approach is adopted to investigate the trajectories of charged particles in the electromagnetic field of kinetic Alfven wave. Expressions are found for the dispersion relation, growth/damping rate and associated currents in the presence of electron beam in homogenous plasma. Kinetic effects of electrons and ions are included to study kinetic Alfven wave because both are important in the transition region. The plasma parameters appropriate to plasma sheet boundary layer are used. It is found that downward electron beam affects the dispersion relation, growth/damping-rate and associated currents in cold electron limit.

Keywords: magnetospheric physics, plasma waves and instabilities, electron beam, space plasma physics, wave-particle interactions

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Authors: J. Gonzalez, P. Jimenez, C. Isaza

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Palms have different characteristics that make them vulnerable; that is the case of the Chamaedorea linearis, with the presence of solitary stems of small diameter and medium leaves, culturally harvested, and in religious festivities used. Additionally, they present a weak apical meristem as the only emergency point, slow development and growth, and an affectation due to the high rate of deforestation in Colombia. Propagation of this species can improve the pressure on wild populations and help their survival in the environment. In this study was used in 177 plants biosolids humus from the Wastewater Treatment Plant (WWTP), located at the UMNG Campus Cajica (Cundinamarca, Colombia). The experiment used a control and two treatments with 10% and 20% of humus. During the process, the variables evaluated were number of leaves, percentage of chlorophyll, stem length, and estimated leaf area. The data set were taking during 14 weeks before the reproductive maturity, evidencing that the most representative development of the palms was in the treatment of 20%, plants in this treatment presented major number of leaves, larger stems, a high quantity of chlorophyll, and was a first treatment that present pinnate leaves them represent an important point in maturity process. The research gives an opportunity to improve times of growth in another species of palms and plants (Product result from INV ING 2986 UMNG).

Keywords: biosolids, humus, growth, palms, wastewater treatment plant, WWTP

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Authors: Mncedisi Trinity Dewa, Andre Francois Van Der Merwe, Stephen Matope

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Tool, Die and Mould-making (TDM) firms have been known to play a pivotal role in the growth and development of the manufacturing sectors in most economies. Their output contributes significantly to the quality, cost and delivery speed of final manufactured parts. Unfortunately, the South African Tool, Die and Mould-making manufacturers have not been competing on the local or global market in a significant way. This reality has hampered the productivity and growth of the sector thus attracting intervention. The paper explores the shortcomings South African toolmakers have to overcome to restore their competitive position globally. Results from a global benchmarking survey on the tooling sector are used to establish a roadmap of what South African toolmakers can do to become a productive, World Class force on the global market.

Keywords: competitive performance objectives, toolmakers, world-class manufacturing, lead times

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Authors: Roaa Sait, Richard Cross

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The synthesis and characterization of one dimensional nanostructure such as nanowires has received considerable attention. Much effort has concentrated on TiN material especially in the biological field due to its useful and unique properties in this field. Therefore, for the purpose of this project, synthesis of Titanium Nitride (TiN) nanowires (NWs) will be presented. They will be synthesised by growing titanium dioxide (Ti) NWs in an aqueous solution at low temperatures under atmospheric pressure. Then the grown nanowires will undergo a 'Nitrodation process' in which results in the formation of TiN NWs. The structure, morphology and composition of the grown nanowires will be characterized using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and Cyclic Voltammetry (CV). Obtaining TiN NWs is a challenging task since it has not been formulated before, as far as we acknowledge. This might be due to the fact that nitriding Ti NWs can be difficult in terms of optimizing experimental parameters.

Keywords: nanowires, dissolution-growth, nucleation, PECVD, deposition, spin coating, scanning electron microscopic analysis, cyclic voltammetry analysis

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Authors: Ruixin Zhang, Joel Carboni, Songchenchen Gong

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Since the Sustainable Development Goals (SDGs) officially became the 17 development goals set by the United Nations in 2015, it has become an inevitable trend in project management development globally. Since Sustainability and glob-alization are the main focus and trends in the 21st century, project management contains system-based optimization, and or-ganizational humanities, environmental protection, and economic development. As a populous country globally, with the advanced development of economy and technology, China becomes one of the biggest markets in the wine industry. However, the develop-ment of society also brings specific environmental issues. Climate changes have already brought severe impacts on the Chinese wine market, including consumer behavior, wine production activities, and organizational humanities. Therefore, the implementation of sustainable project management in Chinese wine market is essential. Surveys based analysis is the primary method to interpret how the climate variation effect the Chinese wine market and the importance of sustainable project management implementation for green market growth in China. This paper proposes the CWW Conceptual model that can be used in the wine industry, the new 7 Drivers Model, and SPM Framework to interpret the main drivers that impact project management implementation in the wine industry and to offer the directions to wine companies in China which would help them to achieve the green growth.

Keywords: project management, sustainability, green growth, climate changes, Chinese wine market

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Authors: Wang Mimi, Jiang Changjun, Liu Guanjun, Fang Xianwen

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Loop structure often appears in the business process modeling, analyzing the consistency of corresponding workflow net models containing loop structure is a problem, the existing behavior consistency methods cannot analyze effectively the process models with the loop structure. In the paper, by analyzing five kinds of behavior relations of transitions, a three-dimensional figure and two-dimensional behavior relation matrix are proposed. Based on this, analysis method of behavior consistency of business process based on Petri net branching processes is proposed. Finally, an example is given out, which shows the method is effective.

Keywords: workflow net, behavior consistency measures, loop, branching process

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Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

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The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

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Authors: Tariq Ahmad Dar, Moinuddin, M. Masroor A. Khan

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There is considerable need in enhancing the content and yield of active constituents of medicinal plants keeping in view their massive demand worldwide. Different strategies have been employed to enhance the active constituents of medicinal plants and the use of phytohormones has been proved effective in this regard. Gamma-irradiated Sodium alginate (ISA) is known to elicit an array of plant defense responses and biological activities in plants. Considering the medicinal importance, a pot experiment was conducted to explore the effect of ISA and phosphorus on growth, yield and quality of fenugreek (Trigonella foenum-graecum L.). ISA spray treatments (0, 40, 80 and 120 mg L-1) were applied alone and in combination with 40 kg P ha-1 (P40). Crop performance was assessed in terms of plant growth characteristics, physiological attributes, seed yield and the content of seed trigonelline. Of the ten-treatments, P40 + 80 mg L−1 of ISA proved the best. The results showed that foliar spray of ISA alone or in combination with P40 augmented the plant vegetative growth, enzymatic activities, trigonelline content, trigonelline yield and economic yield of fenugreek. Application of 80 mg L−1 of ISA applied with P40 gave the best results for almost all the parameters studied compared to control or to 80 mg L−1 of ISA applied alone. This treatment increased the total content of chlorophyll, carotenoids, leaf -N, -P and -K and trigonelline compared to the control by 24.85 and 27.40%, 15 and 23.52%, 18.70 and 16.84%, 15.88 and 18.92%, 12 and 14.44%, at 60 and 90 DAS respectively. The combined application of 80 mg L−1 of ISA along with P40 resulted in the maximum increase in seed yield, trigonelline content and trigonelline yield by146, 34 and 232.41%, respectively, over the control. Gel permeation chromatography revealed the formation of low molecular weight fractions in ISA samples, containing even less than 20,000 molecular weight oligomers, which might be responsible for plant growth promotion in this study. Trigonelline content was determined by reverse phase high performance liquid chromatography (HPLC) with C-18 column.

Keywords: gamma-irradiated sodium alginate, phosphorus, gel permeation chromatography, HPLC, trigonelline content, yield

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Authors: Elisabeth Maidl

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The interdependence of climate change and natural hazard goes along with large uncertainties regarding future risks. Regional stakeholders, experts in natural hazards management and scientists have specific knowledge, resp. mental models on such risks. This diversity of views makes it difficult to find common and broadly accepted prevention measures. If the specific knowledge of these types of actors is shared in an interactive knowledge production process, this enables a broader and common understanding of complex risks and allows to agree on long-term solution strategies. Previous studies on mental models confirm that actors with specific vulnerabilities perceive different aspects of a topic and accordingly prefer different measures. In bringing these perspectives together, there is the potential to reduce uncertainty and to close blind spots in solution finding. However, studies that examine the mental models of regional actors on future concrete mass movement risks are lacking so far. The project tests and evaluates the feasibility of knowledge co-creation for the anticipatory prevention of climate change-induced mass movement risks in the Alps. As a key element, mental models of the three included groups of actors are compared. Being integrated into the research program Climate Change Impacts on Alpine Mass Movements (CCAMM2), this project is carried out in two Swiss mountain regions. The project is structured in four phases: 1) the preparatory phase, in which the participants are identified, 2) the baseline phase, in which qualitative interviews and a quantitative pre-survey are conducted with actors 3) the knowledge-co-creation phase, in which actors have a moderated exchange meeting, and a participatory modelling workshop on specific risks in the region, and 4) finally a public information event. Results show that participants' mental models are based on the place of origin, profession, believes, values, which results in narratives on climate change and hazard risks. Further, the more intensively participants interact with each other, the more likely is that they change their views. This provides empirical evidence on how changes in opinions and mindsets can be induced and fostered.

Keywords: climate change, knowledge-co-creation, participatory process, natural hazard risks

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Authors: Sibylle Tellenbach, Julie Haddock-Millar, Francis Bidault

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The aim of this research is to understand the extent to which hybrid working models have influenced employee engagement in the Swiss financial sector. The context for this research is the transition out of the pandemic and the changes that have occurred between 2020 and 2023. Since the pandemic, many financial services companies have had to rethink their working model for office-based employees, as this group of employees has been able to experience a new way of working and, thus, greater freedom and flexibility. For a large number of companies, it was a huge change to shift from the traditional office-based to a new hybrid working model. A heightened focus on employee engagement has become a necessity in order to understand and respond to the challenges presented by the shift in a working model. This new way of working, partly office-based and partly virtual, has led to ambiguities about the impact on the engagement of hybrid teams. Therefore, the research question is: How hybrid working models have influenced employee engagement to what extent? The methodological approach is a narrative inquiry with four similar functional teams within four Swiss financial companies. Semi-structured interviews will be conducted with managers from middle management and their individual team members. The findings will demonstrate whether this shift in the working model influenced individual team members’ engagement and to what extent. The contribution of this research is two-fold. First, the research makes a theoretical contribution, presenting evidence of the impact of hybrid working on individual team members’ engagement in a specific sector and context, enhancing current knowledge on the challenges in working model transition. Second, this research will make a practice-based contribution, recommending ways to enhance the engagement of hybrid teams in a specific context. These recommendations may be applied in wider sectors and teams.

Keywords: employee engagement, hybrid teams, hybrid working models, Swiss financial sector, team engagement

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Authors: Shreya Sirohi, Vineeta Sirohi

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In the 21st century, the nature of work has become quite complex and dynamic, and in response to this, the organizational culture continues to change and develop new perspectives. Organizational culture and leadership are important elements of any organization. Organization’s performance and success to a large extent, depend upon these two factors. The ability of a leader lies in confronting with the challenge of evolving and adapting the culture of the organization as per the situational demands. Leadership and organizational culture are conceptually intertwined. Leadership is a key ingredient for the successful transformation of any organization, and a favorable organizational culture helps to motivate the employees towards their work. Organizational culture and leadership style plays a crucial role in achieving the specified objectives of an organization. The harmony between culture and leader within organization undoubtedly affects relationships, processes, and employee performance. The present investigation aimed to study the Leadership style and Organisational Culture of private organizations and the relationship between the two. The study was carried out on a sample of 100 employees from five private organizations located in the cities of Gurgaon and Delhi in India. The data was collected by employing organisational culture profile and multifactor leadership questionnaire. The findings of the study indicate that the selected organizations had dominant transformation leadership style, whereas the organizational culture varied from one organization to another. However, technocratic culture was found to be prominent, followed by entrepreneurial organizational culture. A low positive correlation was found between leadership style and organizational culture. The transformational leaders have a positive and significant relationship with employee’s satisfaction, productivity, and organization’s culture. The leaders practicing transformational leadership style inspire their followers, are innovative and are aware of their needs as well as of their followers. Such leadership style has a positive impact both on employees and working culture. Employees of such organization are able to come up with innovative ideas and are efficient in handling situations and making effective decisions. However, low correlation is self indicative of the fact that a single leadership style or a single culture type alone cannot contribute solely towards the growth of an organization. There is a need to blend the culture types and leadership styles suiting the needs of the organization. Organisational culture represents the deeper values and beliefs of the employees and influences organizational performance; hence, the leader has a crucial role to play in creating and managing organizational culture in aligning to the requirements of the present era of competitiveness, globalization and technological advancement.

Keywords: leadership style, organizational culture, technocratic, transformational

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Authors: Josip Visković, Ana Rimac Smiljanić, Ines Ivić

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Housing loans play an important role in CEE countries’ economies. This fact is based on their share in total loans to households and their importance for economic activity and growth in CEE countries. Therefore, it is important to find out key determinants of housing loans demand in these countries. The aim of this study is to research and analyze the determinants of the demand for housing loans in Croatia. In this regard, the effect of economic activity, loan terms and real estate prices were analyzed. Also, the aim of this study is to find out what motivates people to take housing loans. Therefore, primarily empirical study was conducted among the Croatian residents. The results show that demand for housing loans is positively affected by economic growth, higher personal income and flexible loan terms, while it is negatively affected by interest rate rise.

Keywords: CEE countries, Croatia, demand determinants, housing loans

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Authors: Abdul Matin, Muazzama Akhtar, Shahid Nisar, Saddaf Mazzar, Umer Rashid

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Antibiotic resistance is an increasing concern worldwide now a day. Neisseria gonorrhea and Staphylococcus aureus are known to cause major human sexually transmitted and respiratory diseases respectively. Nanotechnology is an emerging discipline and its application in various fields especially in medical sciences is gigantic. In the present study, we synthesized multi-walled carbon nanotubes (MWNTs) using acid oxidation method and solubilized MWNTs were with length predominantly >500 nm and diameters ranging from 40 to 50 nm. The locally synthesized MWNTs were used against gram positive and negative bacteria to determine their impact on bacterial growth. Clinical isolates of Neisseria gonorrhea (isolate: 4C-11) and Staphylococcus aureus (isolate: 38541) were obtained from local hospital and normally cultured in LB broth at 37°C. Both clinical strains can be obtained on request from University of Gujarat. Spectophometric assay was performed to determine the impact of MWNTs on bacterial growth in vitro. To determine the effect of MWTNs on test organisms, various concentration of MWNTs were used and recorded observation on various time intervals to understand the growth inhibition pattern. Our results demonstrated that MWNTs exhibited toxic effects to Staphylococcus aureus while showed very limited growth inhibition to Neisseria gonorrhea, which suggests the resistant potential of Neisseria against nanoparticles. Our results clearly demonstrate the gradual decrease in bacterial numbers with passage of time when compared with control. Maximum bacterial inhibition was observed at maximum concentration (50 µg/ml). Our future work will include further characterization and mode of action of our locally synthesized MWNTs. In conclusion, we investigated and reported for the first time the inhibitory potential of locally synthesized MWNTs on local clinical isolates of Staphylococcus aureus and Neisseria gonorrhea.

Keywords: antibacterial activity, multi walled carbon nanotubes, Neisseria gonorrhea, spectrophotometer assay, Staphylococcus aureus

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Authors: Paolo Russu

Abstract:

The purpose of the present paper is to highlight some features of an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system. In particular, we show that the economy, which is based on a Perfect-Substitution Technologies function of production, has no neither indeterminacy nor poverty trap. This implies that equilibrium select by economy depends on the history (initial values of state variable) of the economy rather than on expectations of economies agents. Moreover, by contrast, we prove that the basin of attraction of locally equilibrium points may be very large, as they can extend up to the boundary of the system phase space. The infinite-horizon optimal control problem has the purpose of maximizing the representative agent’s instantaneous utility function depending on leisure and consumption.

Keywords: Hopf bifurcation, open-access natural resources, optimal control, perfect-substitution technologies, Poincarè compactification

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Authors: Toni Raurich-Marcet, Joan Llonch-Andreu

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This research is focused on the relationship between Search Engine Marketing (SEM) and traditional advertising. The dominant assumption is that SEM does not help brand awareness and only does it in session as if it were the cost of manufacturing the product being sold. The study is methodologically developed using an experiment where the effects were determined to analyze the billboard effect. The research allowed the cross-linking of theoretical and empirical knowledge on digital marketing. This paper has validated this marketing generates retention as traditional advertising would by measuring brand awareness and its improvements. This changes the way performance and brand campaigns are split within marketing departments, effectively rebalancing budgets moving forward.

Keywords: attribution, performance marketing, SEM, marketplaces

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Authors: Natasha Lalla

Abstract:

The impact of free trade on growth has been highly debated and studies have generated varying results. Since the 1970s the Caribbean has engaged in asymmetrical trade with some European states characterized by the Lomé Conventions (1975-1999). These agreements allowed for Caribbean products such as sugar and banana to enter some European countries duty-free and above market prices. With the onset of the World Trade Organization by the mid-1990s, the EU’s banana trade regime was considered illegitimate. Lomé was replaced by the Cotonou agreement (2000-2007), in order to phase out preferences and ensure that the Caribbean trade arrangements were consistent with the international economic environment of trade liberalization. This agreement facilitated signing of the Economic Partnership Agreement in 2008 by both trade blocs whereby Caribbean states must implement freer trade by 2033. The current study is an exploration of how the Organization of the Eastern Caribbean States, the smallest, economically and ecologically vulnerable states of the Caribbean have restructured their trade policies towards the end of preferences and what has been the economic developmental impact of this. This is done by analyzing key reports to understand how these states restructured policies towards freer trade. Secondly, to determine the impact of this, data collected for specific economic indicators were analyzed in a fixed effects panel data framework for the period 1979-2016 on six states of the Organization of the Eastern Caribbean States. The study, therefore, found that freer trade has resulted in negative growth in these states.

Keywords: free trade, growth, OECS, small island developing states

Procedia PDF Downloads 194